Inductive Learning of Fuzzy Regression Trees
نویسنده
چکیده
In this paper we present a novel approach to datadriven fuzzy modeling which aims to create highly accurate but also easily comprehensible models. This goal is obtained by defining a flexible but expressive language automatically from the data. This language is then used to inductively learn fuzzy regression trees from the data. Finally, we present a detailed comparison study on the performance of the proposed method and an outlook to future developments.
منابع مشابه
FS-LiRT—An Inductive Learning Method for Creating Comprehensible Fuzzy Regression Trees
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تاریخ انتشار 2005